How severe is CVE-2026-73627?

No CVSS score has been assigned to CVE-2026-73627 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by CVE-2026-73627?

CVE-2026-73627 affects the following packages: jupyterlab (PyPI), jupyterlab (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2026-73627?

Update jupyterlab to 4.6.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-73627 is resolved across your whole dependency graph.

How do I detect CVE-2026-73627 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterlab, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate CVE-2026-73627 if there is no patch (or I can't update yet)?

If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Is CVE-2026-73627 actively exploited in the wild?

No public exploit code has been indexed for CVE-2026-73627 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2026-73627?

CVE-2026-73627 has an EPSS (Exploit Prediction Scoring System) score of 0.4%, placing it in the 35th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2026-73627?

CVE-2026-73627 is classified as CWE-602 (CWE-602). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was CVE-2026-73627 published, and has it been updated?

CVE-2026-73627 was published on August 13, 2026 and was last updated on October 20, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

Not in CISA KEV

CVE-2026-73627 — jupyterlab

Fix: jupyterlab/jupyterlab#19184

CVE-2026-73627 is a CWE-602 vulnerability in jupyterlab. A fix is available for jupyterlab — see the affected versions and patch details below.

JupyterLab 4.6.0 Plugin Manager Lock-Rule Enforcement Bypass

Also known asBIT-jupyterlab-2026-73627GHSA-h5v5-8746-g7mm

Published

Aug 13, 2026

Updated

Oct 20, 2026

Affected

2 pkgs

Patched

2 / 2

Exploits

None indexed

Exploitation data as of Oct 23, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-73627.

EPSS Exploitation Probability

via FIRST.org ↗

0.4%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs35th percentile — riskier than 35% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

2 pkgs affected

🐍jupyterlab🐍jupyterlab

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

Users could workaround the plugin manager lock rules via direct API access for either:

child plugins of extensions covering multiple plugins
when "lock all" was issued by the administrator

The integrity of data can be impacted, and any hardening or restrictions on permitted user actions (e.g. download/upload limits) within the single-user server can be circumvented if those were implemented with plugins that were locked using the faulty mechanisms.

Patches

JupyterLab v4.6.2 and v4.5.10 contain the patch.

Users of applications that depend on JupyterLab, such as Notebook v7+, should update jupyterlab package too.

Workarounds

Manually lock all plugins that should be locked. The core plugin identifiers can be found in the documentation and identifiers for all installed extensions are listed in the Plugin Manager.

Affected Packages

2 total 2 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`jupyterlab`	≥ 4.6.0&&< 4.6.2	4.6.2`pip install --upgrade 'jupyterlab==4.6.2'`
🐍PyPI	`jupyterlab`	≥ 4.1.0&&< 4.5.10	4.5.10`pip install --upgrade 'jupyterlab==4.5.10'`

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for jupyterlab, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update jupyterlab to 4.6.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-73627 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatModerate

This Moderate severity flaw in JupyterLab allows an authenticated user to circumvent administrative plugin lock rules. Direct API requests can enable or disable plugins intended to be locked, impacting data integrity and bypassing security restrictions in Red Hat OpenShift AI and Migration Toolkit for Applications…

Workaround published by Red Hat

Lock each plugin individually with jupyter labextension lock <plugin-id> instead of “lock all” or locking only a parent multi-plugin extension. That is the GHSA workaround until you upgrade.

Source: Red Hat security advisory for CVE-2026-73627 (CC BY 4.0)

Product	Fixed in	Advisory
Red Hat OpenShift AI 2.25	`rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9:1788315638`	RHSA-2026:65126
Red Hat OpenShift AI 2.25	`rhoai/odh-feature-server-rhel9:1792148523`	RHSA-2026:87410
Red Hat OpenShift AI 3.3	`rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9:1790331087`	RHSA-2026:73987
Red Hat OpenShift AI 3.4	`rhoai/odh-feature-server-rhel9:1791863220`	RHSA-2026:84734

Frequently Asked Questions

JupyterLab's plugin manager exposes administrator controls intended to prevent users from enabling or disabling selected plugins. Two server-side enforcement gaps let an authenticated user bypass those controls with direct requests to `/lab/api/plugins`. ### Impact Users could workaround the plugin manager lock rules via direct API access for either: - child plugins of extensions covering multiple plugins - when "lock all" was issued by the administrator The integrity of data can be impacted, and any hardening or restrictions on permitted user actions (e.g. download/upload limits) within th